多参数融合的球磨机振动特征提取方法

Vibration characteristics extraction of the ball mill based on multi-parameter fusion

  • 摘要: 针对单信号特征参数不能准确表征球磨机负荷状态的问题,采用时域统计分析方法和AR模型方法提取球磨机振动的时域特征参数和频域特征参数,并利用D-S证据理论用于融合振动信号的时域和频域特征参数,并计算每个特征参数的基本概率分布函数.将基本概率分布函数值作为球磨机负载状态的特征值,建立多振动特征参数的特征向量模型.结果表明,多振动特征参数的特征向量模型能很好地表征球磨机负荷状态,为球磨机负荷预测提供数据支持.

     

    Abstract: In view of the problem that the load state of the ball mill cannot be accurately characterized by a single-signal characteristic parameter, statistical analysis and AR model are used to help extract the time domain characteristic parameter and frequency domain characteristic parameter of the ball mill's vibration signal. Then, the D-S evidence theory is also adopted to analyze the two parameters, and the basic probability distribution function of each characteristic parameter is calculated. Finally, the basic probability distribution function value is taken as the characteristic value of the ball mill in load state, and the characteristic vector model of multi-vibration characteristic parameter is established. The results show that this model can well characterize the load state of the ball mill and provide data supporting for the prediction of the load of the ball mill.

     

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